A methodology for procedural piano music composition with mood templates using genetic algorithms

Santos, Laurie R.; Silla, Carlos N.; Abreu, Márjory Da Costa

doi:10.1049/icp.2021.1435

Cited by 4 publications

(1 citation statement)

References 13 publications

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“…In the first type, the fitness function is a mathematical equation used for optimizing the musical rules. For instance, an AI-AMG system by [16] has used the GA method (referred to as "Conventional GA" in this article) to compose monophonic piano music with an emotion profile matching the emotion profile of the input music template. The fitness function used here computes a distance metric (mathematical equation) representing the difference in the emotional content of composed and input music pieces.…”

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confidence: 99%

AI-Based Affective Music Generation Systems: A Review of Methods, and Challenges

Dash¹,

Agres²

2023

Preprint

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Music is a powerful medium for altering the emotional state of the listener. In recent years, with significant advancement in computing capabilities, artificial intelligence-based (AI-based) approaches have become popular for creating affective music generation (AMG) systems that are empowered with the ability to generate affective music. Entertainment, healthcare, and sensor-integrated interactive system design are a few of the areas in which AI-based affective music generation (AI-AMG) systems may have a significant impact.Given the surge of interest in this topic, this article aims to provide a comprehensive review of AI-AMG systems. The main building blocks of an AI-AMG system are discussed, and existing systems are formally categorized based on the core algorithm used for music generation. In addition, this article discusses the main musical features employed to compose affective music, along with the respective AI-based approaches used for tailoring them. Lastly, the main challenges and open questions in this field, as well as their potential solutions, are presented to guide future research. We hope that this review will be useful for readers seeking to understand the state-of-the-art in AI-AMG systems, and gain an overview of the methods used for developing them, thereby helping them explore this field in the future.

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confidence: 99%

AI-Based Affective Music Generation Systems: A Review of Methods, and Challenges

Dash¹,

Agres²

2023

Preprint

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MGEPM: Specific Composition Style Melody Generation Based on Music Gene Expression Programming

Zhou,

Luo,

Yuan

et al. 2024

2024 10th International Conference on Big Data and Information Analytics (BigDIA)

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AI-Based Affective Music Generation Systems: A Review of Methods and Challenges

Dash,

Agres

2024

ACM Comput. Surv.

View full text Add to dashboard Cite

Music is a powerful medium for altering the emotional state of the listener. In recent years, with significant advancements in computing capabilities, artificial intelligence-based (AI-based) approaches have become popular for creating affective music generation (AMG) systems. Entertainment, healthcare, and sensor-integrated interactive system design are a few of the areas in which AI-based affective music generation (AI-AMG) systems may have a significant impact. Given the surge of interest in this topic, this article aims to provide a comprehensive review of controllable AI-AMG systems. The main building blocks of an AI-AMG system are discussed, and existing systems are formally categorized based on the core algorithm used for music generation. In addition, this article discusses the main musical features employed to compose affective music, along with the respective AI-based approaches used for tailoring them. Lastly, the main challenges and open questions in this field, as well as their potential solutions, are presented to guide future research. We hope that this review will be useful for readers seeking to understand the state-of-the-art in AI-AMG systems, and gain an overview of the methods used for developing them, thereby helping them explore this field in the future.

show abstract

A methodology for procedural piano music composition with mood templates using genetic algorithms

Abstract: 2021). A methodology for procedural piano music composition with mood templates using genetic algorithms.

Cited by 4 publications

References 13 publications

AI-Based Affective Music Generation Systems: A Review of Methods, and Challenges

AI-Based Affective Music Generation Systems: A Review of Methods, and Challenges

MGEPM: Specific Composition Style Melody Generation Based on Music Gene Expression Programming

AI-Based Affective Music Generation Systems: A Review of Methods and Challenges

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